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Transfer Learning Model for Target Segment Generation on Sequential Behavior and Advertisement Interaction History

Published: 07 September 2023 Publication History

Abstract

Online advertisement is a key methodology to increase a company’s RoI (Return on Investment). With the recent success of deep learning, many approaches generate target segments by predicting who will click the advertisement from their advertisement interaction history (e.g., user A clicked/did not click advertisement B at time t). However, from their sequential behavior history (e.g., user A interacted with item B with a rating value at time t), we can notice that users could click the advertisement out of short-period curiosity or by accident even though their rating on this specific item was low. Unfortunately, many recommendation approaches will still believe that this user has an interest in the item because in these models the user’s sequential behavior history is neglected. We believe that considering both the user’s sequential behavior on the advertised item and advertisement interaction behavior together will help us to decide the user’s advertisement click willingness. Thus, in this paper, we propose a model that first learns the user’s item preference (rating) information using the transformer model on the sequential behavior history. Finally, we transfer the learned item preference information and train the model to predict the item advertisement click willingness of users on advertisement interaction history. The experiment results on real-world data, containing information on more than twenty-eight million users, have verified that using both a sequential behavior and advertisement interaction history performs better than considering just advertisement interaction history.

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  1. Transfer Learning Model for Target Segment Generation on Sequential Behavior and Advertisement Interaction History

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    ICMLC '23: Proceedings of the 2023 15th International Conference on Machine Learning and Computing
    February 2023
    619 pages
    ISBN:9781450398411
    DOI:10.1145/3587716
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 07 September 2023

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    Author Tags

    1. advertisement interaction
    2. sequential behavior
    3. transfer-learning
    4. transformer

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